502 search results - page 30 / 101 » Principal Component Analysis for Sparse High-Dimensional Dat... |
IDA
1998
Springer
13 years 8 months ago
1998
Springer
A fast and simple algorithm for approximately calculating the principal components (PCs) of a data set and so reducing its dimensionality is described. This Simple Principal Compo...
CVPR
2004
IEEE
14 years 10 months ago
2004
IEEE
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
NIPS
2003
13 years 10 months ago
2003
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
CVPR
2009
IEEE
14 years 20 days ago
2009
IEEE
Face detection plays an important role in many vision applications. Since Viola and Jones [1] proposed the first real-time AdaBoost based object detection system, much effort has ...
CVPR
2003
IEEE
14 years 10 months ago
2003
IEEE
When performing subspace modelling of data using Principal Component Analysis (PCA) it may be desirable to constrain certain directions to be more meaningful in the context of the...